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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2011 - 4

 HIGH-IMPACT PAPER 

PID Neural Network Based Speed Control of Asynchronous Motor using Programmable Logic Controller

MARABA, V. A. See more information about MARABA, V. A. on SCOPUS See more information about MARABA, V. A. on IEEExplore See more information about MARABA, V. A. on Web of Science, KUZUCUOGLU, A. E. See more information about KUZUCUOGLU, A. E. on SCOPUS See more information about KUZUCUOGLU, A. E. on SCOPUS See more information about KUZUCUOGLU, A. E. on Web of Science
 
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Download PDF pdficon (431 KB) | Citation | Downloads: 322 | Views: 8,117

Author keywords
control, neural network, PID, PIDNN, PLC

References keywords
control(12), neural(6), system(5), networks(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2011-11-30
Volume 11, Issue 4, Year 2011, On page(s): 23 - 28
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.04004
Web of Science Accession Number: 000297764500004
SCOPUS ID: 84856594182

Abstract
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This paper deals with the structure and characteristics of PID Neural Network controller for single input and single output systems. PID Neural Network is a new kind of controller that includes the advantages of artificial neural networks and classic PID controller. Functioning of this controller is based on the update of controller parameters according to the value extracted from system output pursuant to the rules of back propagation algorithm used in artificial neural networks. Parameters obtained from the application of PID Neural Network training algorithm on the speed model of the asynchronous motor exhibiting second order linear behavior were used in the real time speed control of the motor. Programmable logic controller (PLC) was used as real time controller. The real time control results show that reference speed successfully maintained under various load conditions.


References | Cited By

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 13 [View]
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Cited-By SCOPUS

SCOPUS® Times Cited: 17
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Cited-By CrossRef

[1] Decentralized PID neural network control for a quadrotor helicopter subjected to wind disturbance, Chen, Yan-min, He, Yong-ling, Zhou, Min-feng, Journal of Central South University, ISSN 2095-2899, Issue 1, Volume 22, 2015.
Digital Object Identifier: 10.1007/s11771-015-2507-9
[CrossRef]

[2] Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules, Zhang, Zhen, Ma, Cheng, Zhu, Rong, Sensors, ISSN 1424-8220, Issue 10, Volume 16, 2016.
Digital Object Identifier: 10.3390/s16101709
[CrossRef]

[3] PID control algorithm based on multistrategy enhanced dung beetle optimizer and back propagation neural network for DC motor control, Kong, Weibin, Zhang, Haonan, Yang, Xiaofang, Yao, Zijian, Wang, Rugang, Yang, Wenwen, Zhang, Jiachen, Scientific Reports, ISSN 2045-2322, Issue 1, Volume 14, 2024.
Digital Object Identifier: 10.1038/s41598-024-79653-z
[CrossRef]

[4] Achievement of Automatic Copper Wire Elongation System, Lin, Hsiung-Cheng, Cheng, Chung-Hao, Algorithms, ISSN 1999-4893, Issue 5, Volume 12, 2019.
Digital Object Identifier: 10.3390/a12050105
[CrossRef]

[5] A PID Parameter Tuning Method Based on the Improved QUATRE Algorithm, Zhao, Zhuo-Qiang, Liu, Shi-Jian, Pan, Jeng-Shyang, Algorithms, ISSN 1999-4893, Issue 6, Volume 14, 2021.
Digital Object Identifier: 10.3390/a14060173
[CrossRef]

[6] A Novel Method for Inverter Faults Detection and Diagnosis in PMSM Drives of HEVs based on Discrete Wavelet Transform, AKTAS, M., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 12, 2012.
Digital Object Identifier: 10.4316/AECE.2012.04005
[CrossRef] [Full text]

[7] Design of Sesame Peeling Machine and Performance Analysis with Threshold-Based Image Segmentation Technique, Gündoğdu, Ahmet, Acar, Emrullah, Çelikel, Reşat, European Journal of Technic, ISSN 2536-5010, Issue 1, Volume 14, 2024.
Digital Object Identifier: 10.36222/ejt.1448580
[CrossRef]

[8] Adaptive neural network PID controller for nonlinear systems, Bouzaiene, Ramzi, Hafsi, Sami, Bouani, Faouzi, 2021 IEEE 2nd International Conference on Signal, Control and Communication (SCC), ISBN 978-1-6654-0270-5, 2021.
Digital Object Identifier: 10.1109/SCC53769.2021.9768352
[CrossRef]

[9] A solution for study of PID controllers using cRIO system, Rata, Gabriela, Rata, Mihai, 2015 9th International Symposium on Advanced Topics in Electrical Engineering (ATEE), ISBN 978-1-4799-7514-3, 2015.
Digital Object Identifier: 10.1109/ATEE.2015.7133685
[CrossRef]

[10] ADRC Based on Artificial Neural Network for a Six-rotor UAV, Xi, Lin, Shao, Yunfeng, Zou, Suli, Ma, Zhongjing, 2021 40th Chinese Control Conference (CCC), ISBN 978-9-8815-6380-4, 2021.
Digital Object Identifier: 10.23919/CCC52363.2021.9549308
[CrossRef]

[11] A solution for study of positioning control of two axes, Rata, Mihai, Rata, Gabriela, 2016 International Conference and Exposition on Electrical and Power Engineering (EPE), ISBN 978-1-5090-6129-7, 2016.
Digital Object Identifier: 10.1109/ICEPE.2016.7781419
[CrossRef]

[12] A solution for the study and understanding of PID controllers, Rata, Mihai, Rata, Gabriela, Chatziathanasiou, Vasilis, 2014 International Conference and Exposition on Electrical and Power Engineering (EPE), ISBN 978-1-4799-5849-8, 2014.
Digital Object Identifier: 10.1109/ICEPE.2014.6969893
[CrossRef]

[13] Improving PID Control Based on Neural Network, Li, Jun, Gomez-Espinosa, Alfonso, 2018 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE), ISBN 978-1-5386-9190-8, 2018.
Digital Object Identifier: 10.1109/ICMEAE.2018.00042
[CrossRef]

[14] Design of Fishhook Wiring Mechanical System based on Automatic Control Process, Wu, Chih-Yang, Lin, Hsiung-Cheng, 2019 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), ISBN 978-1-7281-1651-8, 2019.
Digital Object Identifier: 10.1109/SNPD.2019.8935695
[CrossRef]

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